Research

If you are interested to know more about our research or are looking for possibilities to join our group, please do not hesitate to contact us.

We also offer opportunities for Bachelor and Master projects.

Growth and Metabolism of Living Cells

We develop computational approaches to describe and analyze cellular metabolism. We are interested in interpolating between constraint-based methods and kinetic models of metabolism and growth. To this end, we have developed methods based on parameter sampling and probabilistic descriptions of metabolism.

Of particular interest is the question of ’evolutionary optimality’. That is, to what extend can cellular adaptations be understood by the concept of optimality, and what are the trade-offs between growth and other cellular objectives. We use the perspective of (optimal) resource allocation to understand cellular adaptations. We are also interested in the regulation and dynamics of metabolism.

Further Reading:

Understanding Phototrophic Growth

Cyanobacteria are phototrophic prokaryotes and an integral part of global biogeochemical cycles. Cyanobacteria are the evolutionary inventors of oxygenic photosynthesis, gave rise to plants as endosymbionts, and thereby fundamentally transformed our planet. Understanding the limits of cyanobacterial phototrophic growth directly relates to pertinent questions about climate change and shifts in ecosystem functions.

Key research questions include the stoichiometric reconstruction of cyanobacterial metabolism, its comparison across different strains (microbial diversity), the coordination of cyanobacterial metabolism in dynamic environments, in particular diurnal light/dark cycles, as well as optimal resource allocation for phototrophic growth.

Further Reading:

Cyanobacterial Biotechnology

Due to their capability to assimilate atmospheric CO2 into organic carbon cyanobacteria are interesting host organisms for green biotechnology. The aim is to integrate photosynthetic solar energy conversion and product synthesis into a single biological process. High-quality reconstructions of cyanobacterial metabolism are used to guide and support experimental efforts to increase and sustain product yield and culture productivity. We are also interested in the biological and environmental factors that ultimately limit maximal phototrophic production. The group participated in launching a start-up company to commercialize cultivation of cyanobacteria and microalgae at ultra-high densities (CellDEG).

Further Reading:

Self-Organization of Microbial Communities

No microbe lives isolation, and microbial physiology and growth can only be understood in the context of interactions within an ecosystem. We are particularly interested in how interactions between phototrophic and heterotrophic microbes emerge. To this end, we make use of models of cellular resource allocation that explain how cells co-evolve with an environment that is itself a product of their metabolism. Our hypothesis is that microbial communities self-organize into “super-organisms” that give rise to the complex interactions and dependencies we observe today. Model systems include marine ecosystems, filamentous cyanobacteria, as well as microbial mats.

Further Reading:

Models of Cancer Metabolism

Many diseases are closely linked to changes in cellular metabolism and growth. In particular, shifts in metabolism are a long recognized as a hallmark of cancer, with many cancer cells undergoing significant metabolic reprogramming, such as a shift towards aerobic glycolysis and increased proliferation. We build computational models to understand the observed transitions, in particular for liver metabolism in the context of LiSyM cancer and the project SMART-NAFLD.

Further Reading:

Principles of Cellular Signal Transduction

Noise and fluctuations are ubiquitous in living systems. Still, the interaction between complex regulatory networks and the inherent fluctuations (’noise’) is still insufficiently understood. To elucidate the interrelation between noise and function, we investigate the implications of stochastic fluctuations on cellular regulatory systems, such as signal transduction networks, circadian clocks, or cell cycle control systems. Previous work includes the investigation of the effects of noise on a model of the eukaryotic cell cycle. The stochastic description leads to qualitative changes in the dynamic behavior, such as the emergence of noise-induced oscillations. Current research is focused on a better understanding of robust and reliable information processing in living cells.

Further Reading:

Large-Scale Data Analysis and Interpretation of Metabolomics Data

Metabolomic measurements provide a wealth of information about the biochemical status of cells, tissues and organs and play an important role to elucidate the function of novel genes. A remarkable inherent feature of cellular metabolism is that the concentrations of a small but significant number of metabolites are strongly correlated when measurements of biological replicates are performed. We seek to elucidate how comparative correlation analysis offers a way to exploit the intrinsic variability of metabolic networks to obtain significant additional information about the physiological state of the system. We are particularly interested in the Mutual Information and other information theoretic measures as a measure of dependencies.

Further Reading:

Selected Funding

  • BMBF Forschungsnetzwerk LiSyM-Krebs: SMART-NAFLD
  • DFG Project: Leben vom Licht: vom Wachstum einer Zelle zu produktiven Ökosystemen, Projektnummer 453048493
  • DFG Research Training Group “Computational Systems Biology” [as associated group]
  • Exist-Gründerstipendium „CellDeg“ (BMBF, Förderkennzeichen 03EGSBE291) [2015-2016]
  • e:Bio CyanoGrowth: Die Organisationsprinzipien des cyanobakteriellen Stoffwechsels“ (BMBF, FKZ 0316192) [2013-2017]
  • Einstein Stiftung Berlin: CyanoMetal
  • e:Bio CYANOSYS II: Systems Biology of Cyanobacterial Biofuel Production (BMBF)
  • EU FP7 STREP: DirectFuel [2010-2014]
  • FORSYS-Partner: Systems Biology of Cyanobacterial Biofuel Production (BMBF) [2008-2012]